Addressing mechanism bias in model-based impact forecasts of new tuberculosis vaccines

Tovar, M. (Universidad de Zaragoza) ; Moreno, Y. (Universidad de Zaragoza) ; Sanz, J. (Universidad de Zaragoza)

Resumen: In tuberculosis (TB) vaccine development, multiple factors hinder the design and interpretation of the clinical trials used to estimate vaccine efficacy. The complex transmission chain of TB includes multiple routes to disease, making it hard to link the vaccine efficacy observed in a trial to specific protective mechanisms. Here, we present a Bayesian framework to evaluate the compatibility of different vaccine descriptions with clinical trial outcomes, unlocking impact forecasting from vaccines whose specific mechanisms of action are unknown. Applying our method to the analysis of the M72/AS01E vaccine trial -conducted on IGRA+ individuals- as a case study, we found that most plausible models for this vaccine needed to include protection against, at least, two over the three possible routes to active TB classically considered in the literature: namely, primary TB, latent TB reactivation and TB upon re-infection. Gathering new data regarding the impact of TB vaccines in various epidemiological settings would be instrumental to improve our model estimates of the underlying mechanisms.

Idioma: Inglés

DOI: 10.1038/s41467-023-40976-6

Año: 2023

Publicado en: Nature communications 14, 5312 (2023), 12
ISSN: 2041-1723

Factor impacto JCR: 14.7 (2023)

Categ. JCR: MULTIDISCIPLINARY SCIENCES rank: 8 / 134 = 0.06 (2023) - Q1 - T1

Factor impacto CITESCORE: 24.9 - Biochemistry, Genetics and Molecular Biology (all) (Q1) - Chemistry (all) (Q1) - Physics and Astronomy (all) (Q1)

Factor impacto SCIMAGO: 4.887 - Biochemistry, Genetics and Molecular Biology (miscellaneous) (Q1) - Physics and Astronomy (miscellaneous) (Q1) - Chemistry (miscellaneous) (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/B49-23R-NeuroBioSys
Financiación: info:eu-repo/grantAgreement/ES/DGA/E36-23R-FENOL
Financiación: info:eu-repo/grantAgreement/ES/DGA-IIU/796-2019
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2019-106859GA-I00
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2020-115800GB-I00
Financiación: info:eu-repo/grantAgreement/ES/MICINN/RYC-2017-23560

Tipo y forma: Article (Published version)

Área (Departamento): Área Física Teórica (Dpto. Física Teórica)